Network analysis of mineralogical systems

Abstract

A fundamental goal of mineralogy and petrology is the deep understanding of mineral phase relationships and the consequent spatial and temporal patterns of mineral coexistence in rocks, ore bodies, sediments, meteorites, and other natural polycrystalline materials. The multi-dimensional chemical complexity of such mineral assemblages has traditionally led to experimental and theoretical consideration of 2-, 3-, or n-component systems that represent simplified approximations of natural systems. Network analysis provides a dynamic, quantitative, and predictive visualization framework for employing "big data" to explore complex and otherwise hidden higher-dimensional patterns of diversity and distribution in such mineral systems. We introduce and explore applications of mineral network analysis, in which mineral species are represented by nodes, while coexistence of minerals is indicated by lines between nodes. This approach provides a dynamic visualization platform for higher-dimensional analysis of phase relationships, because topologies of equilibrium phase assemblages and pathways of mineral reaction series are embedded within the networks. Mineral networks also facilitate quantitative comparison of lithologies from different planets and moons, the analysis of coexistence patterns simultaneously among hundreds of mineral species and their localities, the exploration of varied paragenetic modes of mineral groups, and investigation of changing patterns of mineral occurrence through deep time. Mineral network analysis, furthermore, represents an effective visual approach to teaching and learning in mineralogy and petrology.

Analysis and visualization of vanadium mineral diversity and distribution

“…Characteristics of these mineral species, including their physical properties, chemical compositions, and their localities of occurrence, have been parsed into large mineral databases (e.g., rruff.info/ima and mindat.org). These mineralogical "big data" reveal diversity and spatial distribution of all terrestrial minerals (Hazen et al 2015a(Hazen et al , 2015b(Hazen et al , 2016a(Hazen et al , 2016bHystad et al 2015aHystad et al , 2015bHystad et al , 2016, facilitate network analysis of existing minerals (Morrison et al, 2017), and lead to predictions of Earth's "missing" minerals (Hazen et al 2016a;Grew et al 2016;Liu et al, 2016).…”

“…V 5+ minerals are generally of oxidative hydrothermal and weathering origin, and the majority of them are vanadates. In V 4+ minerals, V is mostly present as VO 2+ , which can co-occur with V 3+ , vanadate ion (VO 4 Network analysis has been recently applied to study the diversity and distribution of terrestrial minerals (Morrison et al, 2017). Quantification of network metrics, together with clustering analysis, can not only visualize mineral coexistence, but also reveal hidden topologies and phase relations in a mineral network.…”

Using Visual Exploratory Data Analysis to Facilitate Collaboration and Hypothesis Generation in Cross-Disciplinary Research

“…The case studies in the next section will illustrate a few visualization outputs of this kind, such as the co-relations between primary and secondary cobalt minerals shown in Figure 5. Another relevant DTDI research of network analysis and visualization [35] also revealed a similar EDA approach but applied different techniques. Those visualization results and recognized patterns were used in research discussions and to support decision-making.…”

Origraph: Interactive Network Wrangling

“…We use the term operation, as we frame operations from the perspective of what a network wrangling system should support. In our elicitation, we reflected upon published task lists for visual graph analysis [29,43,50]; related systems that support limited aspects of graph wrangling [8,20,32] our own experiences working with domain experts on graph analysis [8,27,31,36,[42][43][44][47][48][49] and those of colleagues [13,41,51,65, for example]; and an informal task analysis that we conducted with new collaborators [3,4,28,37,38]. Through an iterative, dialogical approach among the co-authors that involved discussions, written summaries, and design sketches, we considered the myriad of literature and experiential sources in determining the range of operations for wrangling and reshaping networks that are, or could be, useful for analysts.…”